• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.503-512
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• 2006

In this paper, the Inverse Weibull distribution parameters have been estimated using a new estimation technique based on the non-parametric kernel density function that introduced as an alternative and reliable technique for estimation in life testing models. This technique will require bootstrapping from a set of sample observations for constructing the density functions of pivotal quantities and thus the confidence intervals for the distribution parameters. The performances of this technique have been studied comparing to the conditional inference on the basis of the mean lengths and the covering percentage of the confidence intervals, via Monte Carlo simulations. The simulation results indicated the robustness of the proposed method that yield reasonably accurate inferences even with fewer bootstrap replications and it is easy to be used than the conditional approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.70.3-70
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• 2001

In this paper, we suggest a kernel level multi thread web accelerator (called the SCALA-AX), which significantly improves the performance of the web soerver. In comparison with a conventional proxy web cache that is generally called a caching server and a simple content-copy based system, the primary functions and goals of SCALA-AX are designed to maximize the content services of a front end web server with high performance. Specifically, the SCALA-AX runs on the kernel level of a web sorrel, based on the newest caching techniques. Moreover, the SCALA-AX supports the http 1.1 protocol and allows the dynamic pages as well as static pages to be processed.

• East Asian mathematical journal
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• v.25 no.1
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• pp.55-68
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• 2009

In this paper we propose new large-update primal-dual inte-rior point algorithms for $P_*(\kappa)$ linear complementarity problems(LCPs). New search directions and proximity measures are proposed based on the kernel function$\psi(t)=\frac{t^{p+1}-1}{p+1}+\frac{e^{\frac{1}{t}}-e}{e}$,$p{\in}$[0,1]. We showed that if a strictly feasible starting point is available, then the algorithm has $O((1+2\kappa)(logn)^{2}n^{\frac{1}{p+1}}log\frac{n}{\varepsilon}$ complexity bound.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.5
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• pp.787-797
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• 1986

An implicit approach is employed to obtain a general boundary integral formulation of axisymmetric elastic problems in terms of a pair of singular integral equations. The corresponding kernel functions from the solutions of Navier's equation are derived by applying a three dimensional integral and a direct axisymmetrical approach. A numerical discretization schem including the evaluation of Cauchy principal values of the singular integral is described. Finally the typical axisymmetric elastic models are analyzed, i.e. the hollow sphere, the constant thickness and the V-notched round bar.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.655-660
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• 2003

In general, Support Vector Machine has a good performance in binary classification, but it has the limitation on multi-pattern classification. So, we proposed an Import Vector Voting model for two or more labels classification. This model applied kernel bagging strategy to Import Vector Machine by Zhu. The proposed model used a voting strategy which averaged optimal kernel function from many kernel functions. In experiments, not only binary but multi-pattern classification problems, our proposed Import Vector Voting model showed good performance for given machine learning data.

• Genomics & Informatics
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• v.20 no.2
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• pp.17.1-17.11
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• 2022

Genetic associations have been quantified using a number of statistical measures. Entropy-based mutual information may be one of the more direct ways of estimating the association, in the sense that it does not depend on the parametrization. For this purpose, both the entropy and conditional entropy of the phenotype distribution should be obtained. Quantitative traits, however, do not usually allow an exact evaluation of entropy. The estimation of entropy needs a probability density function, which can be approximated by kernel density estimation. We have investigated the proper sequence of procedures for combining the kernel density estimation and entropy estimation with a probability density function in order to calculate mutual information. Genotypes and their interactions were constructed to set the conditions for conditional entropy. Extensive simulation data created using three types of generating functions were analyzed using two different kernels as well as two types of multifactor dimensionality reduction and another probability density approximation method called m-spacing. The statistical power in terms of correct detection rates was compared. Using kernels was found to be most useful when the trait distributions were more complex than simple normal or gamma distributions. A full-scale genomic dataset was explored to identify associations using the 2-h oral glucose tolerance test results and γ-glutamyl transpeptidase levels as phenotypes. Clearly distinguishable single-nucleotide polymorphisms (SNPs) and interacting SNP pairs associated with these phenotypes were found and listed with empirical p-values.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1011-1018
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• 2006

Due to rapid development of mobile communication terminals and various requests of their users, multimedia information including image information has been the basis of mobile communication contents. In order to use vectored image information efficiently, which is more favorable than bit-mapped image information when transmission delay time and costs are considered, efficient vector graphics supporting systems are needed. Therefore, vector graphics kernel systems have been proposed and standardization attempts have been made in order to increase interoperability. In this paper, a vector graphics kernel based on OpenVG is designed and implemented. OpenVG was proposed as a standard vector graphics kernel by Khronos Group recently. The implemented vector graphics kernel, named by alexVG, is developed on a PC emulator as well as on a development board equipped with an ARM processor. In addition, performance tests are made in order to verify its functions.

• Journal of the Korean Mathematical Society
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• v.42 no.5
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• pp.975-1002
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• 2005

On the setting of the upper half-space H of the Eu­clidean n-space, we show the boundedness of weighted Bergman projection for 1 < p < $\infty$ and nonorthogonal projections for 1 $\leq$ p < $\infty$ . Using these results, we show that Bergman norm is equiva­ lent to the normal derivative norms on weighted harmonic Bergman spaces. Finally, we find the dual of b$\_{$^{1}$.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.2
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• pp.1-10
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• 1995

Since there is currently no commercial protocol simulator for CDMA mobile communication system, we need to develop a General-Purposed Protocol Test Simulator (G-PTS). This paper is concerned with the design and implementation of this G-PTS contains the multi-scenario generating functions, multi-tasking kernel and multiple interface functions. Thus it can be utilized in the test category using multiple base-stations such as soft-handoff, 3-way handoff and mulit-party call features. G-PTS is verified using the model of CDMA soft handoff scenario and the result shows its reliable operations.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.193-199
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• 2005

A simple method is proposed to detect the number of change points with jump discontinuities in nonparamteric regression functions. The proposed estimators are based on a local linear regression fit by the comparison of left and right one-side kernel smoother. Also, the proposed methodology is suggested as the test statistic for detecting of change points and the direction of jump discontinuities.